===========
INTAKE2STAC
===========
.. image:: https://codebase.helmholtz.cloud/cat4kit/tds2stac/-/raw/main/intake2stac.png
=========
.. image:: https://img.shields.io/pypi/v/intake2stac.svg
:target: https://pypi.python.org/pypi/intake2stac
.. image:: https://readthedocs.org/projects/intake2stac/badge/?version=latest
:target: https://intake2stac.readthedocs.io/en/latest/?version=latest
:alt: Documentation Status
STAC specification is a method of exposing spatial and temporal data collections in a standardized manner. Specifically, the `SpatioTemporal Asset Catalog (STAC) <https://stacspec.org/en>`_ specification describes and catalogs spatiotemporal assets using a common structure.
This package creates STAC metadata by harvesting dataset details from the `INTAKE <https://intake.readthedocs.io/en/latest/index.html>`_ interface. After creating STAC Catalogs, Collections, and Items, it imports them into `pgSTAC <https://stac-utils.github.io/pgstac/pgstac/>`_ and `STAC-FastAPI <https://stac-utils.github.io/stac-fastapi/>`_.
* Free software: EUPL-1.2
* Documentation: https://intake2stac.readthedocs.io.
Installation from PyPi
------------------------
.. code:: bash
pip install intake2stac
Installation for development
--------------------------------
.. code:: bash
git clone https://codebase.helmholtz.cloud/cat4kit/intake2stac.git
cd intake2stac
python -m venv venv
source venv/bin/activate
pip install -r requirements_dev.txt
Installing using Docker
------------------------
For runnig by docker use `this <https://codebase.helmholtz.cloud/cat4kit/ds2stac-docker>`_ repository.
Usage
----------------
Use case:
You can use the following template for creating STAC catalog from the TDS web service for your project.
You can change configuration of PgSTAC in `config_pgstac <./intake2stac/config_pgstac.py>`_
.. code::python
from intake2stac import intake2stac
intake2stac.Convertor(
"https://s3.imk-ifu.kit.edu:8082/climatedata/catalog.yaml",
driver="zarr",
stac=True or False,
stac_id="an ID for the main STAC catalog",
stac_description="Description for the main STAC catalog",
stac_dir="/path/to/save/stac/catalogs/",
stac_catalog_dynamic=True or False,
)
.. code::python
output:
Intake catalog details:
Version: 0.1
Drivers: Zarr
Parameter: mswx v1.0e | Description: MSWX global climate data | urlpath: https://s3.imk-ifu.kit.edu:8082/climatedata/mswx_daily_v1.0.zarr
Parameter: eobs v24.0e | Description: E-OBS v24.0e climate data for Europe | urlpath: https://s3.imk-ifu.kit.edu:8082/climatedata/eobs_v24.0e.zarr
Parameter: MERRA2 tavgM 2d aer NX | Description: M2TMNXAER (or tavgM_2d_aer_Nx) is a time-averaged 2-dimensional monthly mean data collection in Modern-Era
Retrospective analysis for Research and Applications version 2 (MERRA-2). This collection consists of assimilated aerosol diagnostics, such as column mass density
of aerosol components (black carbon, dust, sea salt, sulfate, and organic carbon), surface mass concentration of aerosol components, and total extinction (and scattering )
aerosol optical thickness (AOT) at 550 nm. The total PM1.0, PM2.5, and PM10 may be derived with the formula described in the FAQs under the Documentation tab of
this page. The collection also includes variance of certain parameters. | urlpath: https://s3.imk-ifu.kit.edu:8082/climatedata/merra2_monthly_tavgM_2d_aer_Nx.zarr
Parameter: ERA5 daily surface variables | Description: Selection of surface variables (precip, temperature, etc.) from ECMWFs latest atmospheric reanalysis ERA5
| urlpath: https://s3.imk-ifu.kit.edu:8082/climatedata/era5_daily.zarr
./mswx v1.0e/collection.json
|____ ./mswx_v1.0e/mswx_v1.0e.json
./eobs v24.0e/collection.json
|____ ./eobs_v24.0e/eobs_v24.0e.json
./MERRA2 tavgM 2d aer NX/collection.json
|____ ./MERRA2_tavgM_2d_aer_NX/MERRA2_tavgM_2d_aer_NX.json
./ERA5 daily surface variables/collection.json
|____ ./ERA5_daily_surface_variables/ERA5_daily_surface_variables.json
Copyright
---------
Copyright © 2023 Karlsruher Institut für Technologie
Licensed under the EUPL-1.2-or-later
This program is distributed in the hope that it will be useful, but WITHOUT ANY
WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A
PARTICULAR PURPOSE. See the EUPL-1.2 license for more details.
You should have received a copy of the EUPL-1.2 license along with this
program. If not, see https://www.eupl.eu/.
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"description": "===========\nINTAKE2STAC\n===========\n\n\n.. image:: https://codebase.helmholtz.cloud/cat4kit/tds2stac/-/raw/main/intake2stac.png\n\n\n=========\n\n.. image:: https://img.shields.io/pypi/v/intake2stac.svg\n :target: https://pypi.python.org/pypi/intake2stac\n\n\n.. image:: https://readthedocs.org/projects/intake2stac/badge/?version=latest\n :target: https://intake2stac.readthedocs.io/en/latest/?version=latest\n :alt: Documentation Status\n\n\n\nSTAC specification is a method of exposing spatial and temporal data collections in a standardized manner. Specifically, the `SpatioTemporal Asset Catalog (STAC) <https://stacspec.org/en>`_ specification describes and catalogs spatiotemporal assets using a common structure. \nThis package creates STAC metadata by harvesting dataset details from the `INTAKE <https://intake.readthedocs.io/en/latest/index.html>`_ interface. After creating STAC Catalogs, Collections, and Items, it imports them into `pgSTAC <https://stac-utils.github.io/pgstac/pgstac/>`_ and `STAC-FastAPI <https://stac-utils.github.io/stac-fastapi/>`_.\n\n* Free software: EUPL-1.2\n* Documentation: https://intake2stac.readthedocs.io.\n\n\n\nInstallation from PyPi\n------------------------\n.. code:: bash\n\n pip install intake2stac\n\nInstallation for development\n--------------------------------\n.. code:: bash\n\n git clone https://codebase.helmholtz.cloud/cat4kit/intake2stac.git\n cd intake2stac\n python -m venv venv\n source venv/bin/activate\n pip install -r requirements_dev.txt\n\n\nInstalling using Docker\n------------------------\n\nFor runnig by docker use `this <https://codebase.helmholtz.cloud/cat4kit/ds2stac-docker>`_ repository.\n\n\nUsage\n----------------\n \nUse case:\n\nYou can use the following template for creating STAC catalog from the TDS web service for your project.\n\nYou can change configuration of PgSTAC in `config_pgstac <./intake2stac/config_pgstac.py>`_\n\n.. code::python\n from intake2stac import intake2stac\n intake2stac.Convertor(\n \"https://s3.imk-ifu.kit.edu:8082/climatedata/catalog.yaml\",\n driver=\"zarr\",\n stac=True or False,\n stac_id=\"an ID for the main STAC catalog\",\n stac_description=\"Description for the main STAC catalog\",\n stac_dir=\"/path/to/save/stac/catalogs/\",\n stac_catalog_dynamic=True or False,\n )\n\n.. code::python\n output:\n Intake catalog details:\n Version: 0.1\n Drivers: Zarr\n Parameter: mswx v1.0e | Description: MSWX global climate data | urlpath: https://s3.imk-ifu.kit.edu:8082/climatedata/mswx_daily_v1.0.zarr\n Parameter: eobs v24.0e | Description: E-OBS v24.0e climate data for Europe | urlpath: https://s3.imk-ifu.kit.edu:8082/climatedata/eobs_v24.0e.zarr\n Parameter: MERRA2 tavgM 2d aer NX | Description: M2TMNXAER (or tavgM_2d_aer_Nx) is a time-averaged 2-dimensional monthly mean data collection in Modern-Era \n Retrospective analysis for Research and Applications version 2 (MERRA-2). This collection consists of assimilated aerosol diagnostics, such as column mass density \n of aerosol components (black carbon, dust, sea salt, sulfate, and organic carbon), surface mass concentration of aerosol components, and total extinction (and scattering )\n aerosol optical thickness (AOT) at 550 nm. The total PM1.0, PM2.5, and PM10 may be derived with the formula described in the FAQs under the Documentation tab of \n this page. The collection also includes variance of certain parameters. | urlpath: https://s3.imk-ifu.kit.edu:8082/climatedata/merra2_monthly_tavgM_2d_aer_Nx.zarr\n Parameter: ERA5 daily surface variables | Description: Selection of surface variables (precip, temperature, etc.) from ECMWFs latest atmospheric reanalysis ERA5 \n | urlpath: https://s3.imk-ifu.kit.edu:8082/climatedata/era5_daily.zarr\n ./mswx v1.0e/collection.json\n |____ ./mswx_v1.0e/mswx_v1.0e.json\n ./eobs v24.0e/collection.json\n |____ ./eobs_v24.0e/eobs_v24.0e.json\n ./MERRA2 tavgM 2d aer NX/collection.json\n |____ ./MERRA2_tavgM_2d_aer_NX/MERRA2_tavgM_2d_aer_NX.json\n ./ERA5 daily surface variables/collection.json\n |____ ./ERA5_daily_surface_variables/ERA5_daily_surface_variables.json\n\n\nCopyright\n---------\nCopyright \u00a9 2023 Karlsruher Institut f\u00fcr Technologie\n\nLicensed under the EUPL-1.2-or-later\n\nThis program is distributed in the hope that it will be useful, but WITHOUT ANY\nWARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A\nPARTICULAR PURPOSE. See the EUPL-1.2 license for more details.\n\nYou should have received a copy of the EUPL-1.2 license along with this\nprogram. If not, see https://www.eupl.eu/.\n\n",
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